Upload app (17).py

app (17).py

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+import gradio as gr
+import PIL
+import cv2
+import numpy as np
+from src.deoldify import device
+from src.deoldify.device_id import DeviceId
+from src.deoldify.visualize import *
+from src.app_utils import get_model_bin
+
+device.set(device=DeviceId.CPU)
+
+def load_model(model_dir, option):
+    if option.lower() == 'artistic':
+        model_url = 'https://data.deepai.org/deoldify/ColorizeArtistic_gen.pth'
+        get_model_bin(model_url, os.path.join(model_dir, "ColorizeArtistic_gen.pth"))
+        colorizer = get_image_colorizer(artistic=True)
+    elif option.lower() == 'stable':
+        model_url = "https://www.dropbox.com/s/usf7uifrctqw9rl/ColorizeStable_gen.pth?dl=0"
+        get_model_bin(model_url, os.path.join(model_dir, "ColorizeStable_gen.pth"))
+        colorizer = get_image_colorizer(artistic=False)
+
+    return colorizer
+
+def resize_img(input_img, max_size):
+    img = input_img.copy()
+    img_height, img_width = img.shape[0], img.shape[1]
+
+    if max(img_height, img_width) > max_size:
+        if img_height > img_width:
+            new_width = img_width * (max_size / img_height)
+            new_height = max_size
+            resized_img = cv2.resize(img, (int(new_width), int(new_height)))
+            return resized_img
+        elif img_height <= img_width:
+            new_width = img_height * (max_size / img_width)
+            new_height = max_size
+            resized_img = cv2.resize(img, (int(new_width), int(new_height)))
+            return resized_img
+
+    return img
+
+def colorize_image(input_image, colorizer, img_size=800):
+    pil_img = input_image.convert("RGB")
+    img_rgb = np.array(pil_img)
+    resized_img_rgb = resize_img(img_rgb, img_size)
+    resized_pil_img = PIL.Image.fromarray(resized_img_rgb)
+    output_pil_img = colorizer.plot_transformed_pil_image(resized_pil_img, render_factor=35, compare=False)
+
+    return output_pil_img
+
+def app(input_image, model='Artistic'):
+    # Load models
+    colorizer = load_model('models/', model)
+
+    # Colorize the image
+    output_image = colorize_image(input_image, colorizer)
+
+    return output_image
+
+
+
+title = "<span style='color: #191970;'>Aiconvert.online</span>"
+
+gr.Interface(
+    app, 
+    gr.inputs.Image(type="pil", label="Input"),
+    
+    gr.Image(type="pil", label="Output", show_share_button=False),
+    title=title,
+    css="footer{display:none !important;}",
+    theme=gr.themes.Base(),
+    enable_queue=True,
+    allow_flagging=False
+).launch()